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The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage
(Emerald, 2020-08-04)
Purpose: This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach: In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based partial and general coverage of suppliers makes the number of orders of products more realistic. In this model, the weights of suppliers are determined by fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, as a multi-criteria decision analysis method, in the objective function. Also, the authors consider the parameters related to delays as triangular fuzzy numbers. Findings: A small-sized numerical example is provided to clearly show the proposed model. The exact epsilon constraint method is used to solve this given multi-objective combinatorial optimization problem. Subsequently, the sensitivity analysis is conducted to testify the proposed model. The obtained results demonstrate the validity of the proposed multiple objectives mixed integer mathematical programming model and the efficiency of the solution approach. Originality/value: In real-life situations, supplier selection parameters are uncertain and incomplete. Hence, the fuzzy set theory is used to tackle uncertainty. In this paper, a multi-objective supplier selection problem is formulated taking into consideration the coverage of suppliers and suppliers’ weights. Integrating coverage of suppliers to select and allocate the order to them can be mentioned as the main contribution of this study. The proposed model considers the delay from suppliers as fuzzy parameters.
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The combined use of life cycle assessment and data envelopment analysis to analyse the environmental efficiency of multi-unit systems
(Elsevier, 2022-01-01)
The combination of life cycle assessment (LCA) and data envelopment analysis (DEA) methodologies has been employed over the past years to assess the eco-efficiency of a wide spectrum of production systems. This chapter presents a critical review on current practices of the joint application of LCA+DEA, as well as point towards the methodological challenges and opportunities for the future. Considering the growth of the method in the past decade, it is plausible to assume that an increasing number of studies will continue to appear in the literature. The development of guidance or standardisation reports would constitute a step forward in terms of providing advice on how recurrent methodological issues (e.g. uncertainty, selection of impacts categories or DEA models, etc.) should be addressed in LCA+DEA.
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Sustainability transitions and "bending the curve of biodiversity collapse" in the Amazon Forest
(Cornell University, 2025-06-01)
This paper undertakes an analysis of deforestation in the Amazon area using a pathways-based approach to sustainability. We ground the analysis primarily in the sustainability transitions literature but also draw a bridge with socio-ecological concepts which helps us to understand the nature of transitions in this context. The concept of a deforestation system is developed by examining the interplay of infrastructure, technologies, narratives, and institutions. Drawing on a literature review and an in-depth case study of Puerto Maldonado in Madre de Dios, Peru, the paper identifies three pathways for addressing deforestation: optimisation, natural capital, and regenerative change. We suggest that while the optimisation pathway provides partial solutions through mitigation and compensation strategies, it often reinforces extractivist logics. The study also underscores the limitations of natural capital frameworks, which tend to rely on centralised governance and market-based instruments while lacking broader social engagement. In contrast, our findings emphasise the potential of regenerative strategies rooted in local agency, community-led experimentation, and context-sensitive institutional arrangements. The paper contributes to ongoing debates on biodiversity governance by illustrating how the spatial and long-term dynamics of deforestation interact, and why inclusive, territorially grounded pathways are crucial for bending the curve of biodiversity loss.
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